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MotivationDouble-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases.ResultsHere, we report dsRID (double-stranded RNA identifier), a machine-learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data.Availability and implementationSoftware implementation of dsRID, and genomic coordinates of regions predicted by dsRID in all samples are available at the GitHub repository: https://github.com/gxiaolab/dsRID.

Age is the primary risk factor for many common human diseases. Here, we quantify the relative contributions of genetics and aging to gene expression patterns across 27 tissues from 948 humans. We show that the predictive power of expression quantitative trait loci is impacted by age in many tissues. Jointly modelling the contributions of age and genetics to transcript level variation we find expression heritability (h2) is consistent among tissues while the contribution of aging varies by >20-fold with [Formula: see text] in 5 tissues. We find that while the force of purifying selection is stronger on genes expressed early versus late in life (Medawar's hypothesis), several highly proliferative tissues exhibit the opposite pattern. These non-Medawarian tissues exhibit high rates of cancer and age-of-expression-associated somatic mutations. In contrast, genes under genetic control are under relaxed constraint. Together, we demonstrate the distinct roles of aging and genetics on expression phenotypes.

Developing strategies that promote the resolution of vascular inflammation and atherosclerosis remains a major therapeutic challenge. Here, we show that exosomes produced by naive bone marrow-derived macrophages (BMDM-exo) contain anti-inflammatory microRNA-99a/146b/378a that are further increased in exosomes produced by BMDM polarized with IL-4 (BMDM-IL-4-exo). These exosomal microRNAs suppress inflammation by targeting NF-κB and TNF-α signaling and foster M2 polarization in recipient macrophages. Repeated infusions of BMDM-IL-4-exo into Apoe-/- mice fed a Western diet reduce excessive hematopoiesis in the bone marrow and thereby the number of myeloid cells in the circulation and macrophages in aortic root lesions. This also leads to a reduction in necrotic lesion areas that collectively stabilize atheroma. Thus, BMDM-IL-4-exo may represent a useful therapeutic approach for atherosclerosis and other inflammatory disorders by targeting NF-κB and TNF-α via microRNA cargo delivery.

We demonstrate the general existence of a local dipole conservation law in bosonic field theory. The scalar charge density arises from the symplectic form of the system, whereas the tensor current descends from its stress tensor. The algebra of spatial translations becomes centrally extended in presence of field configurations with a finite nonzero charge. Furthermore, when the symplectic form is closed but not exact, the system may, surprisingly, lack a well-defined momentum density. This leads to a theorem for the presence of additional light modes in the system whenever the short-distance physics is governed by a translationally invariant local field theory. We also illustrate this mechanism for axion electrodynamics as an example of a system with Nambu-Goldstone modes of higher-form symmetries.

Analysis methods based on mode decomposition have been proposed to describe the characteristics of flow phenomena. Among them, proper orthogonal decomposition (POD), which decomposes modes into eigenvalues and basis vectors, has long been used. Many studies have shown that POD is a useful method for capturing the characteristics of unsteady flow. In particular, Snapshot POD has attracted much recent attention and has been used to solve unsteady flow problems. However, the basis vectors of the mode obtained by conventional POD is different for each condition. Therefore, whether the basis vectors of each mode are switching in the direction of parameters (e.g. different shapes or different Reynolds numbers) or whether they develop or decay is difficult to discuss. As a result, discussions on conventional POD tend to be qualitative. To address this issue, the present study uses Parametric Global POD, a method that perfectly matches basis vectors in results with different parameters (in this study, different Reynolds numbers). Parametric Global POD method was applied to the analysis of the flow field in a curved pipe and found to capture the development or decay of modes with major basis vectors in the direction of parameters, which is difficult to achieve with conventional POD methods. [ABSTRACT FROM AUTHOR]

Objective: Dementia with Lewy bodies (DLB) is recognized as the second most common cause of degenerative dementia in older people with Alzheimer's disease (AD), and distinguishing between these 2 diseases may be challenging in clinical practice. However, accurate differentiation is important because these 2 diseases have different prognoses and require different care. Recently, several studies have reported that neuromelanin-sensitive MRI can detect neurodegeneration in the substantia nigra pars compacta (SNc). DLB patients are considered to demonstrate degeneration and a reduction of dopaminergic neurons in the SNc. Therefore, neuromelanin-sensitive MRI may be useful for the diagnosis of DLB. Therefore, in this study, we aimed to investigate the usefulness of neuromelanin-sensitive MRI in the distinguishing DLB from AD. Methods: A total of 21 probable DLB and 22 probable AD patients were enrolled. All participants underwent both DaT-SPECT and neuromelanin-sensitive MRI. A combined model of neuromelanin-sensitive MRI and Dopamine transporter single-photon emission computed tomography (DaT-SPECT) was created using logistic regression analysis (forced entry method). Results: There was no difference in the diagnostic utility of neuromelanin-sensitive MRI and DaT-SPECT in distinguishing DLB from AD. There was no significant correlation between the results of neuromelanin-sensitive MRI and DaT-SPECT in DLB patients. The combination of neuromelanin-sensitive MRI and DaT-SPECT demonstrated higher diagnostic performance in distinguishing between DLB and AD compared with neuromelanin-sensitive MRI alone. Additionally, although the combination of both modalities showed a larger AUC compared with DaT-SPECT alone, the difference was not statistically significant. Conclusions: Neuromelanin-sensitive MRI may be equally or even more useful than DaT-SPECT in the clinical differentiation of DLB from AD. Furthermore, the combination of neuromelanin-sensitive MRI and DaT-SPECT may be a highly sensitive imaging marker for distinguishing DLB from AD. [ABSTRACT FROM AUTHOR]